THREE NOVEL SPIKE DETECTION APPROACHES FOR NOISY NEURONAL DATA

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AAZAMI HAMED; Sanei Saeid

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Seminar Paper

Paper Information

Seminar: INTERNATIONAL CONFERENCE ON COMPUTER AND KNOWLEDGE ENGINEERING (ICCKE)
Year:2014 | Issue:4

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Title

THREE NOVEL SPIKE DETECTION APPROACHES FOR NOISY NEURONAL DATA

Author(s)

AAZAMI HAMED | Sanei Saeid

Keywords

SPIKE DETECTION

FRACTAL DIMENSION

NONLINEAR ENERGY OPERATOR

STANDARD DEVIATION

SAVITZKY-GOLAY FILTER

DISCRETE WAVELET TRANSFORM

Abstract

IN THIS PAPER THREE NEW METHODS BASED ON SMOOTHED NONLINEAR ENERGY OPERATOR (SNEO), FRACTAL DIMENSION (FD) AND STANDARD DEVIATION TO DETECT THE SPIKES FOR NOISY NEURONAL DATA ARE PROPOSED. IN MANY CASES, ESPECIALLY WHEN THERE ARE SEVERAL NOISE SOURCES, THESE METHODS MAY NOT BE ACCEPTABLE AS SPIKE DETECTORS. TO OVERCOME THIS PROBLEM, WE USE SAVITZKY-GOLAY FILTER AND DISCRETE WAVELET TRANSFORM (DWT) AS PRE-PROCESSING STEPS. RESULTS SHOW THAT WHEN THERE IS TOO MUCH NOISE IN THE SIGNAL, THE PROPOSED METHOD USING THE STANDARD DEVIATION AND DWT CAN DETECT THE SPIKES BETTER THAN THE OTHER METHODS. THE AVERAGE DETECTION RATE AND FALSE DETECTION OF SPIKES FOR THE PROPOSED METHOD BASED ON STANDARD DEVIATION AND DWT ARE RESPECTIVELY 100% AND 43% FOR SEMI-REAL SIGNALS WITH SNR=-5 DB.

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APA: Copy

AAZAMI, HAMED, & Sanei, Saeid. (2014). THREE NOVEL SPIKE DETECTION APPROACHES FOR NOISY NEURONAL DATA. INTERNATIONAL CONFERENCE ON COMPUTER AND KNOWLEDGE ENGINEERING (ICCKE). SID. https://sid.ir/paper/926364/en

Vancouver: Copy

AAZAMI HAMED, Sanei Saeid. THREE NOVEL SPIKE DETECTION APPROACHES FOR NOISY NEURONAL DATA. 2014. Available from: https://sid.ir/paper/926364/en

IEEE: Copy

HAMED AAZAMI, and Saeid Sanei, “THREE NOVEL SPIKE DETECTION APPROACHES FOR NOISY NEURONAL DATA,” presented at the INTERNATIONAL CONFERENCE ON COMPUTER AND KNOWLEDGE ENGINEERING (ICCKE). 2014, [Online]. Available: https://sid.ir/paper/926364/en

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